Is your Business Decision-Making a Guessing Game? Business decision-making processes and approaches vary widely. An increasing number of organizations strive to identify critical business decisions to make and then use data-driven approaches to inform their options and support their final choices. However, lack of formality and structure leads to inconsistencies, sub-optimal decisions, and a frequent inability to justify, support, validate, and learn from how critical business decisions are determined. Organizations and business functions that apply structured and formal approaches to business decision making tend to report higher levels of success. The rigor of their approaches allows them to arrive at suitable decisions more often and with higher degrees of confidence than organizations that do not apply any decision-making methodology. Making business decisions data driven and doing so via a structured approach yields significant positive results. Data leaders and their teams can help move the organization toward a state of Hyper-Decisive® decision making by working with key executives and constituents to identify scenarios in which improvements in business decision making can drive substantial value. By introducing changes in both process and approach they can show immediate benefits in the form of more optimal and repeatable decision making. Become a #DataLeader to continue reading this and many more critical thought leadership pieces - https://ow.ly/jPlR50SRFJi #businessintelligence #analytics #data #leadership #dataprivacy
About us
As an independent industry resource, Dresner Advisory Services provides an alternative perspective on information management, business intelligence, analytics, performance management and related markets through the objective, non-sponsored and crowd-sourced Wisdom of Crowds® industry research. Our Wisdom of Crowds® family of research includes our three Wisdom of Crowds® flagship reports, and wide array of thematic reports: - Analytical Data Infrastructure (Flagship) - BI/Analytics Competency Center - Big Data Analytics - Business Intelligence Market Study (Flagship) - Business Intelligence / Analytical Platforms - Cloud Computing and Business Intelligence - Data Catalog and Governance - Data Pipelines and Integration - Data Preparation - Data Science and Machine Learning - Embedded Business Intelligence - Enterprise Performance Management (Flagship) - Financial Close Management - Natural Language Analytics - Sales Performance Management (SPM) - Self-Service BI/Analytics - Small and Mid-Sized Enterprise Business Intelligence - Small and Mid-Sized Enterprise Performance Management
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- Research Services
- Company size
- 11-50 employees
- Type
- Privately Held
- Founded
- 2007
- Specialties
- Thought leadership, strategy advisement, and research products
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Special Report: Tableau versus Microsoft The demand for effective business intelligence and data visualization tools increased as organizations aim to leverage data for improved decision making and operational efficiency. This latest special report examines the offerings and positioning of two major players in the business intelligence market: Tableau (Salesforce) and Microsoft Power BI. Tableau, a Salesforce company, is known for its user-friendly data visualization capabilities. Tableau's platform allows users to create interactive dashboards and perform detailed data analysis. The platform emphasizes ease of use, community support, and integration with various data sources, enabling users to explore and visualize their data effectively. Microsoft Power BI is a business analytics toolset designed to deliver insights across organizations. Power BI integrates seamlessly with Microsoft's products, including Azure and Office 365. The platform is recognized for its ability to handle large datasets, perform real-time data analysis, and offer advanced data modeling. Power BI focuses on providing enterprise-grade analytics, scalability, and collaboration features. This newest Special Report compares Tableau and Microsoft on key aspects such as usability, integration capabilities, performance, scalability, and support. The goal is to provide a clear understanding of how each platform meets the needs of modern enterprises and supports their data-driven initiatives. Become a #DataLeader to continue reading this Special Report and many more critical thought leadership pieces - dresnerdataleaders.com #businessintelligence #dataanalytics #analytics #Tableau #Microsoft
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Special Report: IBM, Oracle, SAP, and Teradata Data Warehouse Platforms The demand for cloud data platforms has increased as organizations look to leverage big data, drive digital transformation, and achieve greater operational agility. The transition from traditional on-premises data warehouses to cloud-based solutions offers advantages such as scalability, flexibility, and cost-efficiency. Our latest special report examines the offerings and positioning of four legacy vendors in the cloud data warehouse space: IBM, Oracle, SAP, Teradata. In an overall view of the market, legacy vendors—typically those that had products available before the onslaught of cloud computing—are frequently pushed to the side, the very fact of their longevity having the effect of making them less shiny and attractive to a new set of buyers. But this typical approach has the effect of overlooking two major strengths that are unique to these legacy vendors. - These legacy database vendors have products which have been in production for longer than the cloud has been in existence and in development, in some cases, for decades. Both the development span, which allows vendors to create truly deep functionality, and the deployment duration, which allowed vendors to work with their enterprise customers to understand issues and address them, contribute to a level of robustness which is not proven in newer, flashier vendors. - These legacy database vendors also have a significant overall market share, based on systems designed and implemented years ago. Moving these systems is nontrivial, and most companies will not move them to other database vendors before they reach their end of life. For legacy systems, this is years, if not decades into the future. Become a #DataLeader to continue reading this Special Report and many more critical thought leadership pieces - dresnerdataleaders.com #datawarehouse #oracle #ibm #SAP #teradata #businessintelligence #data #analytics
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Upsurge in SI and Consultant Use on BI Projects Require a Safety Net. Our latest data show that use and perceived importance of system integrators (SIs) and consultants continues to rise. Organizations increasingly allocate greater percentages of their data and analytics project budgets to the use of SIs and consultants. In addition, expertise matters most when choosing an SI or consultant. And when sourcing that talent, organizations increasingly consider their vendors as trusted advisors that can direct them to the right potential SI and consultant resources to use. Hiring SIs and consultants for an increasing percentage of project responsibilities requires greater expertise in managing the engagements. But in almost no instances—even for the most critical projects—should a data leader look to manage these engagements directly. Instead, a data leader should coordinate as needed with project managers but still primarily focus on influencing the foundations for and use of data and analytics throughout the organization. These data and analytics “guardrails” include data governance principles and programs; data management initiatives such as data integration, data quality, and master data management; guidance on where and when certain analytical techniques are appropriate and which data (and other) sources to use; as well as strategies regarding data availability and use in generative AI. Such prioritization make sense for a data leader—staff handles the granular detail of managing specific (often technically oriented) engagements while the data leader guides proper focus on the principles of Hyper-Decisiveness while data leader guides proper focus on the principles of Hyper-Decisiveness while ensuring initiatives improve the Hyper-Decisive® maturity of the organization. Become a #DataLeader to continue reading this and many more critical thought leadership pieces - https://ow.ly/snk050Sq0JC #businessintelligence #analytics #data #leadership #consultants #systemsintegrators
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